minor changes: removed trailing spaces in some files

This commit is contained in:
Vladimir Dudnik 2011-04-18 19:34:51 +00:00
parent dd45fe13d1
commit 8e7768379f
4 changed files with 92 additions and 93 deletions

View File

@ -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) );

View File

@ -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;

View File

@ -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[] = {

View File

@ -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){