minor changes: removed trailing spaces in some files

modules/features2d/src/surf.cpp

@@ -156,7 +156,7 @@ icvResizeHaarPattern( const int src[][5], CvSurfHF* dst, int n, int oldSize, int
  * Calculate the determinant and trace of the Hessian for a layer of the
  * scale-space pyramid
  */
-CV_INLINE void 
+CV_INLINE void
 icvCalcLayerDetAndTrace( const CvMat* sum, int size, int sampleStep, CvMat *det, CvMat *trace )
 {
     const int NX=3, NY=3, NXY=4;
@@ -184,7 +184,7 @@ icvCalcLayerDetAndTrace( const CvMat* sum, int size, int sampleStep, CvMat *det,
     /* Ignore pixels where some of the kernel is outside the image */
     margin = (size/2)/sampleStep;
 
-    for( i=0; i<samples_i; i++ )
+    for( i = 0; i < samples_i; i++ )
     {
         sum_ptr = sum->data.i + (i*sampleStep)*sum->cols;
         det_ptr = det->data.fl + (i+margin)*det->cols + margin;
@@ -275,9 +275,9 @@ icvFindMaximaInLayer( const CvMat *sum, const CvMat* mask_sum, const CvSURFParam
     CvSurfHF Dm;
     int i, j, size, margin, layer_rows, layer_cols;
     float *det_ptr, *trace_ptr;
- 
+
     size = sizes[layer];
-    
+
     /* The integral image 'sum' is one pixel bigger than the source image */
     layer_rows = (sum->rows-1)/sampleStep;
     layer_cols = (sum->cols-1)/sampleStep;
@@ -287,7 +287,7 @@ icvFindMaximaInLayer( const CvMat *sum, const CvMat* mask_sum, const CvSURFParam
 
     if( mask_sum )
        icvResizeHaarPattern( dm, &Dm, NM, 9, size, mask_sum->cols );
-    
+
     for( i = margin; i < layer_rows-margin; i++ )
     {
         det_ptr = dets[layer]->data.fl + i*dets[layer]->cols;
@@ -309,13 +309,13 @@ icvFindMaximaInLayer( const CvMat *sum, const CvMat* mask_sum, const CvSURFParam
                 const float *det1 = dets[layer-1]->data.fl + i*c + j;
                 const float *det2 = dets[layer]->data.fl   + i*c + j;
                 const float *det3 = dets[layer+1]->data.fl + i*c + j;
-                float N9[3][9] = { { det1[-c-1], det1[-c], det1[-c+1],          
+                float N9[3][9] = { { det1[-c-1], det1[-c], det1[-c+1],
                                      det1[-1]  , det1[0] , det1[1],
                                      det1[c-1] , det1[c] , det1[c+1]  },
-                                   { det2[-c-1], det2[-c], det2[-c+1],       
+                                   { det2[-c-1], det2[-c], det2[-c+1],
                                      det2[-1]  , det2[0] , det2[1],
                                      det2[c-1] , det2[c] , det2[c+1]  },
-                                   { det3[-c-1], det3[-c], det3[-c+1],       
+                                   { det3[-c-1], det3[-c], det3[-c+1],
                                      det3[-1]  , det3[0] , det3[1],
                                      det3[c-1] , det3[c] , det3[c+1]  } };
 
@@ -343,7 +343,7 @@ icvFindMaximaInLayer( const CvMat *sum, const CvMat* mask_sum, const CvSURFParam
                     double center_i = sum_i + (double)(size-1)/2;
                     double center_j = sum_j + (double)(size-1)/2;
 
-                    CvSURFPoint point = cvSURFPoint( cvPoint2D32f(center_j,center_i), 
+                    CvSURFPoint point = cvSURFPoint( cvPoint2D32f(center_j,center_i),
                                                      CV_SIGN(trace_ptr[j]), sizes[layer], 0, val0 );
 
                     /* Interpolate maxima location within the 3x3x3 neighbourhood  */
@@ -352,14 +352,14 @@ icvFindMaximaInLayer( const CvMat *sum, const CvMat* mask_sum, const CvSURFParam
 
                     /* Sometimes the interpolation step gives a negative size etc. */
                     if( interp_ok  )
-                    {   
+                    {
                         /*printf( "KeyPoint %f %f %d\n", point.pt.x, point.pt.y, point.size );*/
                     #ifdef HAVE_TBB
                         static tbb::mutex m;
                         tbb::mutex::scoped_lock lock(m);
-                    #endif                        
+                    #endif
                         cvSeqPush( points, &point );
-                    }    
+                    }
                 }
             }
         }
@@ -381,13 +381,13 @@ struct SURFBuildInvoker
         dets = _dets;
         traces = _traces;
     }
-   
+
     void operator()(const BlockedRange& range) const
-    { 
+    {
         for( int i=range.begin(); i<range.end(); i++ )
             icvCalcLayerDetAndTrace( sum, sizes[i], sampleSteps[i], dets[i], traces[i] );
     }
-    
+
     const CvMat *sum;
     const int *sizes;
     const int *sampleSteps;
@@ -422,7 +422,7 @@ struct SURFFindInvoker
             icvFindMaximaInLayer( sum, mask_sum, params, dets, traces, sizes, layer, 
                                   sampleSteps[layer], points );
         }
-    }    
+    }
 
     const CvMat *sum;
     const CvMat *mask_sum;
@@ -440,7 +440,7 @@ struct SURFFindInvoker
 
 
 /* Wavelet size at first layer of first octave. */ 
-const int HAAR_SIZE0 = 9;    
+const int HAAR_SIZE0 = 9;
 
 /* Wavelet size increment between layers. This should be an even number,
  such that the wavelet sizes in an octave are either all even or all odd.
@@ -468,7 +468,7 @@ static CvSeq* icvFastHessianDetector( const CvMat* sum, const CvMat* mask_sum,
     cv::AutoBuffer<int> sampleSteps(nTotalLayers);
     cv::AutoBuffer<int> middleIndices(nMiddleLayers);
     int octave, layer, step, index, middleIndex;
- 
+
     /* Allocate space and calculate properties of each layer */
     index = 0;
     middleIndex = 0;
@@ -514,17 +514,17 @@ namespace cv
 {
 
 /* Methods to free data allocated in SURFInvoker constructor */
-template<> inline void Ptr<float>::delete_obj(){ cvFree(&obj); }
-template<> inline void Ptr<CvPoint>::delete_obj(){ cvFree(&obj); }
+template<> inline void Ptr<float>::delete_obj()   { cvFree(&obj); }
+template<> inline void Ptr<CvPoint>::delete_obj() { cvFree(&obj); }
 
 struct SURFInvoker
 {
     enum { ORI_RADIUS = 6, ORI_WIN = 60, PATCH_SZ = 20 };
-    
-    static const int ORI_SEARCH_INC;
+
+    static const int   ORI_SEARCH_INC;
     static const float ORI_SIGMA;
     static const float DESC_SIGMA;
-    
+
     SURFInvoker( const CvSURFParams* _params,
                  CvSeq* _keypoints, CvSeq* _descriptors,
                  const CvMat* _img, const CvMat* _sum )
@@ -537,7 +537,7 @@ struct SURFInvoker
 
         /* Simple bound for number of grid points in circle of radius ORI_RADIUS */
         const int nOriSampleBound = (2*ORI_RADIUS+1)*(2*ORI_RADIUS+1);
-        
+
         /* Allocate arrays */
         apt = (CvPoint*)cvAlloc(nOriSampleBound*sizeof(CvPoint));
         aptw = (float*)cvAlloc(nOriSampleBound*sizeof(float));
@@ -567,13 +567,14 @@ struct SURFInvoker
                 DW[i*PATCH_SZ+j] = G_desc.at<float>(i,0) * G_desc.at<float>(j,0);
         }
     }
+
     void operator()(const BlockedRange& range) const
     {
         /* X and Y gradient wavelet data */
         const int NX=2, NY=2;
         const int dx_s[NX][5] = {{0, 0, 2, 4, -1}, {2, 0, 4, 4, 1}};
         const int dy_s[NY][5] = {{0, 0, 4, 2, 1}, {0, 2, 4, 4, -1}};
-        
+
         const int descriptor_size = params->extended ? 128 : 64;
         /* Optimisation is better using nOriSampleBound than nOriSamples for 
          array lengths.  Maybe because it is a constant known at compile time */
@@ -586,7 +587,7 @@ struct SURFInvoker
         CvMat matY = cvMat(1, nOriSampleBound, CV_32F, Y);
         CvMat _angle = cvMat(1, nOriSampleBound, CV_32F, angle);
         CvMat _patch = cvMat(PATCH_SZ+1, PATCH_SZ+1, CV_8U, PATCH);
-        
+
         int k, k1 = range.begin(), k2 = range.end();
         int maxSize = 0;
         for( k = k1; k < k2; k++ )
@@ -649,7 +650,7 @@ struct SURFInvoker
             }
             matX.cols = matY.cols = _angle.cols = nangle;
             cvCartToPolar( &matX, &matY, 0, &_angle, 1 );
-            
+
             float bestx = 0, besty = 0, descriptor_mod = 0;
             for( i = 0; i < 360; i += ORI_SEARCH_INC )
             {
@@ -682,7 +683,7 @@ struct SURFInvoker
             CvMat win = cvMat(win_size, win_size, CV_8U, winbuf->data.ptr);
             float sin_dir = sin(descriptor_dir);
             float cos_dir = cos(descriptor_dir) ;
-            
+
             /* Subpixel interpolation version (slower). Subpixel not required since
              the pixels will all get averaged when we scale down to 20 pixels */
             /*
@@ -798,17 +799,17 @@ struct SURFInvoker
     const CvMat* sum;
     CvSeq* keypoints;
     CvSeq* descriptors;
-    
+
     /* Pre-calculated values */
     int nOriSamples;
-    cv::Ptr<CvPoint> apt; 
-    cv::Ptr<float> aptw;    
+    cv::Ptr<CvPoint> apt;
+    cv::Ptr<float> aptw;
     cv::Ptr<float> DW;
 };
-     
-const int SURFInvoker::ORI_SEARCH_INC = 5;  
-const float SURFInvoker::ORI_SIGMA = 2.5f;
-const float SURFInvoker::DESC_SIGMA = 3.3f;
+
+const int   SURFInvoker::ORI_SEARCH_INC = 5;
+const float SURFInvoker::ORI_SIGMA      = 2.5f;
+const float SURFInvoker::DESC_SIGMA     = 3.3f;
 }
 
 
@@ -870,9 +871,9 @@ cvExtractSURF( const CvArr* _img, const CvArr* _mask,
         cvSeqPushMulti( descriptors, 0, N );
     }
 
-     
-	if ( N > 0 )
-    cv::parallel_for(cv::BlockedRange(0, N),
+
+    if ( N > 0 )
+        cv::parallel_for(cv::BlockedRange(0, N),
                      cv::SURFInvoker(&params, keypoints, descriptors, img, sum) );
 
 

modules/objdetect/src/featurepyramid.cpp

@@ -10,14 +10,15 @@
 #define min(a,b)            (((a) < (b)) ? (a) : (b))
 #endif
 
-static inline int sign(float r){
+static inline int sign(float r)
+{
     if(r >  0.0001f) return  1;
     if(r < -0.0001f) return -1;
     return 0;
 }
 
 /*
-// Getting feature map for the selected subimage  
+// Getting feature map for the selected subimage
 //
 // API
 // int getFeatureMaps(const IplImage * image, const int k, featureMap **map);
@@ -29,7 +30,7 @@ static inline int sign(float r){
 // RESULT
 // Error status
 */
-int getFeatureMaps_dp(const IplImage * image,const int k, CvLSVMFeatureMap **map)
+int getFeatureMaps_dp(const IplImage* image,const int k, CvLSVMFeatureMap **map)
 {
     int sizeX, sizeY;
     int p, px, strsz;

modules/objdetect/src/hog.cpp

@@ -123,7 +123,7 @@ void HOGDescriptor::write(FileStorage& fs, const String& objName) const
 {
     if( !objName.empty() )
         fs << objName;
-    
+
     fs << "{" CV_TYPE_NAME_HOG_DESCRIPTOR
     << "winSize" << winSize
     << "blockSize" << blockSize
@@ -139,7 +139,7 @@ void HOGDescriptor::write(FileStorage& fs, const String& objName) const
         fs << "SVMDetector" << "[:" << svmDetector << "]";
     fs << "}";
 }
-    
+
 bool HOGDescriptor::load(const String& filename, const String& objname)
 {
     FileStorage fs(filename, FileStorage::READ);
@@ -167,12 +167,12 @@ void HOGDescriptor::copyTo(HOGDescriptor& c) const
     c.gammaCorrection = gammaCorrection;
     c.svmDetector = svmDetector;
 }
-    
+
 void HOGDescriptor::computeGradient(const Mat& img, Mat& grad, Mat& qangle,
                                     Size paddingTL, Size paddingBR) const
 {
     CV_Assert( img.type() == CV_8U || img.type() == CV_8UC3 );
-    
+
     Size gradsize(img.cols + paddingTL.width + paddingBR.width,
                   img.rows + paddingTL.height + paddingBR.height);
     grad.create(gradsize, CV_32FC2);  // <magnitude*(1-alpha), magnitude*alpha>
@@ -221,13 +221,13 @@ void HOGDescriptor::computeGradient(const Mat& img, Mat& grad, Mat& qangle,
 #ifdef HAVE_IPP
     Mat lutimg(img.rows,img.cols,CV_MAKETYPE(CV_32F,cn));
     Mat hidxs(1, width, CV_32F);
-    Ipp32f *pHidxs = (Ipp32f*)hidxs.data;
-    Ipp32f *pAngles = (Ipp32f*)Angle.data;
+    Ipp32f* pHidxs  = (Ipp32f*)hidxs.data;
+    Ipp32f* pAngles = (Ipp32f*)Angle.data;
 
     IppiSize roiSize;
     roiSize.width = img.cols;
     roiSize.height = img.rows;
-    
+
     for( y = 0; y < roiSize.height; y++ )
     {
        const uchar* imgPtr = img.data + y*img.step;
@@ -238,22 +238,22 @@ void HOGDescriptor::computeGradient(const Mat& img, Mat& grad, Mat& qangle,
           imglutPtr[x] = lut[imgPtr[x]];
        }
     }
-    
+
 #endif
     for( y = 0; y < gradsize.height; y++ )
     {
 #ifdef HAVE_IPP
-        const float* imgPtr = (float*)(lutimg.data + lutimg.step*ymap[y]);
+        const float* imgPtr  = (float*)(lutimg.data + lutimg.step*ymap[y]);
         const float* prevPtr = (float*)(lutimg.data + lutimg.step*ymap[y-1]);
         const float* nextPtr = (float*)(lutimg.data + lutimg.step*ymap[y+1]);
 #else
-        const uchar* imgPtr = img.data + img.step*ymap[y];
+        const uchar* imgPtr  = img.data + img.step*ymap[y];
         const uchar* prevPtr = img.data + img.step*ymap[y-1];
         const uchar* nextPtr = img.data + img.step*ymap[y+1];
 #endif
         float* gradPtr = (float*)grad.ptr(y);
         uchar* qanglePtr = (uchar*)qangle.ptr(y);
-        
+
         if( cn == 1 )
         {
             for( x = 0; x < width; x++ )
@@ -281,18 +281,18 @@ void HOGDescriptor::computeGradient(const Mat& img, Mat& grad, Mat& qangle,
                 dx0 = p2[2] - p0[2];
                 dy0 = nextPtr[x1+2] - prevPtr[x1+2];
                 mag0 = dx0*dx0 + dy0*dy0;
-                
+
                 dx = p2[1] - p0[1];
                 dy = nextPtr[x1+1] - prevPtr[x1+1];
                 mag = dx*dx + dy*dy;
-                
+
                 if( mag0 < mag )
                 {
                     dx0 = dx;
                     dy0 = dy;
                     mag0 = mag;
                 }
-                
+
                 dx = p2[0] - p0[0];
                 dy = nextPtr[x1] - prevPtr[x1];
                 mag = dx*dx + dy*dy;
@@ -303,18 +303,18 @@ void HOGDescriptor::computeGradient(const Mat& img, Mat& grad, Mat& qangle,
                 dx0 = lut[p2[2]] - lut[p0[2]];
                 dy0 = lut[nextPtr[x1+2]] - lut[prevPtr[x1+2]];
                 mag0 = dx0*dx0 + dy0*dy0;
-                
+
                 dx = lut[p2[1]] - lut[p0[1]];
                 dy = lut[nextPtr[x1+1]] - lut[prevPtr[x1+1]];
                 mag = dx*dx + dy*dy;
-                
+
                 if( mag0 < mag )
                 {
                     dx0 = dx;
                     dy0 = dy;
                     mag0 = mag;
                 }
-                
+
                 dx = lut[p2[0]] - lut[p0[0]];
                 dy = lut[nextPtr[x1]] - lut[prevPtr[x1]];
                 mag = dx*dx + dy*dy;
@@ -334,10 +334,10 @@ void HOGDescriptor::computeGradient(const Mat& img, Mat& grad, Mat& qangle,
         ippsCartToPolar_32f((const Ipp32f*)Dx.data, (const Ipp32f*)Dy.data, (Ipp32f*)Mag.data, pAngles, width);
         for( x = 0; x < width; x++ )
         {
-           if(pAngles[x] < 0.f) pAngles[x]+=(Ipp32f)(CV_PI*2.);
+           if(pAngles[x] < 0.f)
+             pAngles[x] += (Ipp32f)(CV_PI*2.);
         }
 
-         
         ippsNormalize_32f(pAngles, pAngles, width, 0.5f/angleScale, 1.f/angleScale);
         ippsFloor_32f(pAngles,(Ipp32f*)hidxs.data,width);
         ippsSub_32f_I((Ipp32f*)hidxs.data,pAngles,width);
@@ -369,7 +369,7 @@ void HOGDescriptor::computeGradient(const Mat& img, Mat& grad, Mat& qangle,
             hidx++;
             hidx &= hidx < _nbins ? -1 : 0;
             qanglePtr[x*2+1] = (uchar)hidx;
-                    }
+        }
     }
 }
 
@@ -405,7 +405,7 @@ struct HOGCache
 
     const float* getBlock(Point pt, float* buf);
     virtual void normalizeBlockHistogram(float* histogram) const;
-    
+
     vector<PixData> pixData;
     vector<BlockData> blockData;
 
@@ -525,7 +525,7 @@ void HOGCache::init(const HOGDescriptor* _descriptor,
             int icellX1 = icellX0 + 1, icellY1 = icellY0 + 1;
             cellX -= icellX0;
             cellY -= icellY0;
-            
+
             if( (unsigned)icellX0 < (unsigned)ncells.width &&
                 (unsigned)icellX1 < (unsigned)ncells.width )
             {
@@ -626,7 +626,7 @@ const float* HOGCache::getBlock(Point pt, float* buf)
 
     CV_Assert( (unsigned)pt.x <= (unsigned)(grad.cols - blockSize.width) &&
                (unsigned)pt.y <= (unsigned)(grad.rows - blockSize.height) );
-    
+
     if( useCache )
     {
         CV_Assert( pt.x % cacheStride.width == 0 &&
@@ -658,7 +658,7 @@ const float* HOGCache::getBlock(Point pt, float* buf)
     for( k = 0; k < blockHistogramSize; k++ )
         blockHist[k] = 0.f;
 #endif
-    
+
     const PixData* _pixData = &pixData[0];
 
     for( k = 0; k < C1; k++ )
@@ -681,13 +681,13 @@ const float* HOGCache::getBlock(Point pt, float* buf)
         float w, t0, t1, a0 = a[0], a1 = a[1];
         const uchar* h = qanglePtr + pk.qangleOfs;
         int h0 = h[0], h1 = h[1];
-        
+
         float* hist = blockHist + pk.histOfs[0];
         w = pk.gradWeight*pk.histWeights[0];
         t0 = hist[h0] + a0*w;
         t1 = hist[h1] + a1*w;
         hist[h0] = t0; hist[h1] = t1;
-        
+
         hist = blockHist + pk.histOfs[1];
         w = pk.gradWeight*pk.histWeights[1];
         t0 = hist[h0] + a0*w;
@@ -702,13 +702,13 @@ const float* HOGCache::getBlock(Point pt, float* buf)
         float w, t0, t1, a0 = a[0], a1 = a[1];
         const uchar* h = qanglePtr + pk.qangleOfs;
         int h0 = h[0], h1 = h[1];
-        
+
         float* hist = blockHist + pk.histOfs[0];
         w = pk.gradWeight*pk.histWeights[0];
         t0 = hist[h0] + a0*w;
         t1 = hist[h1] + a1*w;
         hist[h0] = t0; hist[h1] = t1;
-        
+
         hist = blockHist + pk.histOfs[1];
         w = pk.gradWeight*pk.histWeights[1];
         t0 = hist[h0] + a0*w;
@@ -750,7 +750,7 @@ void HOGCache::normalizeBlockHistogram(float* _hist) const
     for( i = 0; i < sz; i++ )
         sum += hist[i]*hist[i];
 #endif
-    
+
     float scale = 1.f/(std::sqrt(sum)+sz*0.1f), thresh = (float)descriptor->L2HysThreshold;
 #ifdef HAVE_IPP
     ippsMulC_32f_I(scale,hist,sz);
@@ -772,8 +772,8 @@ void HOGCache::normalizeBlockHistogram(float* _hist) const
         hist[i] *= scale;
 #endif
 }
-    
-    
+
+
 Size HOGCache::windowsInImage(Size imageSize, Size winStride) const
 {
     return Size((imageSize.width - winSize.width)/winStride.width + 1,
@@ -801,7 +801,7 @@ void HOGDescriptor::compute(const Mat& img, vector<float>& descriptors,
     padding.width = (int)alignSize(std::max(padding.width, 0), cacheStride.width);
     padding.height = (int)alignSize(std::max(padding.height, 0), cacheStride.height);
     Size paddedImgSize(img.cols + padding.width*2, img.rows + padding.height*2);
-    
+
     HOGCache cache(this, img, padding, padding, nwindows == 0, cacheStride);
 
     if( !nwindows )
@@ -858,7 +858,7 @@ void HOGDescriptor::detect(const Mat& img,
     hits.clear();
     if( svmDetector.empty() )
         return;
-    
+
     if( winStride == Size() )
         winStride = cellSize;
     Size cacheStride(gcd(winStride.width, blockStride.width),
@@ -867,7 +867,7 @@ void HOGDescriptor::detect(const Mat& img,
     padding.width = (int)alignSize(std::max(padding.width, 0), cacheStride.width);
     padding.height = (int)alignSize(std::max(padding.height, 0), cacheStride.height);
     Size paddedImgSize(img.cols + padding.width*2, img.rows + padding.height*2);
-    
+
     HOGCache cache(this, img, padding, padding, nwindows == 0, cacheStride);
 
     if( !nwindows )
@@ -927,7 +927,7 @@ void HOGDescriptor::detect(const Mat& img,
     }
 }
 
-    
+
 struct HOGInvoker
 {
     HOGInvoker( const HOGDescriptor* _hog, const Mat& _img,
@@ -942,7 +942,7 @@ struct HOGInvoker
         levelScale = _levelScale;
         vec = _vec;
     }
-    
+
     void operator()( const BlockedRange& range ) const
     {
         int i, i1 = range.begin(), i2 = range.end();
@@ -950,7 +950,7 @@ struct HOGInvoker
         Size maxSz(cvCeil(img.cols/minScale), cvCeil(img.rows/minScale));
         Mat smallerImgBuf(maxSz, img.type());
         vector<Point> locations;
-        
+
         for( i = i1; i < i2; i++ )
         {
             double scale = levelScale[i];
@@ -968,7 +968,7 @@ struct HOGInvoker
                                     scaledWinSize.width, scaledWinSize.height));
         }
     }
-    
+
     const HOGDescriptor* hog;
     Mat img;
     double hitThreshold;
@@ -1001,22 +1001,22 @@ void HOGDescriptor::detectMultiScale(
     levelScale.resize(levels);
 
     ConcurrentRectVector allCandidates;
-    
+
     parallel_for(BlockedRange(0, (int)levelScale.size()),
                  HOGInvoker(this, img, hitThreshold, winStride, padding, &levelScale[0], &allCandidates));
-    
+
     foundLocations.resize(allCandidates.size());
     std::copy(allCandidates.begin(), allCandidates.end(), foundLocations.begin());
 
     groupRectangles(foundLocations, groupThreshold, 0.2);
 }
 
-    
+
 typedef RTTIImpl<HOGDescriptor> HOGRTTI;
 
 CvType hog_type( CV_TYPE_NAME_HOG_DESCRIPTOR, HOGRTTI::isInstance,
                  HOGRTTI::release, HOGRTTI::read, HOGRTTI::write, HOGRTTI::clone);
-    
+
 vector<float> HOGDescriptor::getDefaultPeopleDetector()
 {
     static const float detector[] = {

modules/objdetect/src/resizeimg.cpp

@@ -4,8 +4,9 @@
 #include <assert.h>
 #include <math.h>
 
-IplImage * resize_opencv (IplImage * img, float scale){
-    IplImage * imgTmp;
+IplImage* resize_opencv(IplImage* img, float scale)
+{
+    IplImage* imgTmp;
 
     int W, H, tW, tH;
 
@@ -14,14 +15,10 @@ IplImage * resize_opencv (IplImage * img, float scale){
 
     tW = (int)(((float)W) * scale + 0.5);
     tH = (int)(((float)H) * scale + 0.5);
-    
+
     imgTmp = cvCreateImage(cvSize(tW , tH), img->depth, img->nChannels);
-    cvResize(
-       img,
-       imgTmp,
-       CV_INTER_AREA
-    );
-    
+    cvResize(img, imgTmp, CV_INTER_AREA);
+
     return imgTmp;
 }
 
@@ -42,7 +39,7 @@ IplImage * resize_opencv (IplImage * img, float scale){
 //    int i;
 //    for(i = 0; i < n; i++){
 //        dst[ofs[i].di] += ofs[i].alpha * src[ofs[i].si];
-//    }  
+//    }
 //}
 //
 //int round(float val){