Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

minor changes: removed trailing spaces in some files

Browse Source
pull/13383/head
Vladimir Dudnik 14 years ago
parent dd45fe13d1
commit 8e7768379f
4 changed files with 92 additions and 93 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 77
      modules/features2d/src/surf.cpp
  2. 7
      modules/objdetect/src/featurepyramid.cpp
  3. 84
      modules/objdetect/src/hog.cpp
  4. 17
      modules/objdetect/src/resizeimg.cpp

77
modules/features2d/src/surf.cpp
Unescape 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) );

7
modules/objdetect/src/featurepyramid.cpp
Unescape 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;

84
modules/objdetect/src/hog.cpp
Unescape 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[] = {

17
modules/objdetect/src/resizeimg.cpp
Unescape 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){

Write Preview
Loading…
Cancel
Save