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fixed big in gpu::HOGDescriptor, added property into CPU's HOGDescriptor

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This commit is contained in:
Alexey Spizhevoy 2010-11-16 07:40:32 +00:00
parent e954577304
commit cc6a87fc9d
3 changed files with 11 additions and 9 deletions
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8
modules/gpu/src/cuda/hog.cu
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@ -446,7 +446,7 @@ __global__ void compute_gradients_8UC4_kernel(int height, int width, const PtrEl
if (threadIdx.x == 0) if (threadIdx.x == 0)
{ {
val = x > 0 ? row[x - 1] : row[x + 1]; val = x > 0 ? row[x - 1] : row[1];
sh_row[0] = val.x; sh_row[0] = val.x;
sh_row[(nthreads + 2)] = val.y; sh_row[(nthreads + 2)] = val.y;
sh_row[2 * (nthreads + 2)] = val.z; sh_row[2 * (nthreads + 2)] = val.z;
@ -454,7 +454,7 @@ __global__ void compute_gradients_8UC4_kernel(int height, int width, const PtrEl
if (threadIdx.x == blockDim.x - 1) if (threadIdx.x == blockDim.x - 1)
{ {
val = (x < width - 1) ? row[x + 1] : row[x - 1]; val = (x < width - 1) ? row[x + 1] : row[width - 2];
sh_row[blockDim.x + 1] = val.x; sh_row[blockDim.x + 1] = val.x;
sh_row[blockDim.x + 1 + (nthreads + 2)] = val.y; sh_row[blockDim.x + 1 + (nthreads + 2)] = val.y;
sh_row[blockDim.x + 1 + 2 * (nthreads + 2)] = val.z; sh_row[blockDim.x + 1 + 2 * (nthreads + 2)] = val.z;
@ -553,10 +553,10 @@ __global__ void compute_gradients_8UC1_kernel(int height, int width, const PtrEl
sh_row[threadIdx.x + 1] = row[x - 2]; sh_row[threadIdx.x + 1] = row[x - 2];
if (threadIdx.x == 0) if (threadIdx.x == 0)
sh_row[0] = x > 0 ? row[x - 1] : row[x + 1]; sh_row[0] = x > 0 ? row[x - 1] : row[1];
if (threadIdx.x == blockDim.x - 1) if (threadIdx.x == blockDim.x - 1)
sh_row[blockDim.x + 1] = (x < width - 1) ? row[x + 1] : row[x - 1]; sh_row[blockDim.x + 1] = (x < width - 1) ? row[x + 1] : row[width - 2];
__syncthreads(); __syncthreads();
if (x < width) if (x < width)

9
modules/objdetect/include/opencv2/objdetect/objdetect.hpp
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@ -360,20 +360,22 @@ struct CV_EXPORTS_W HOGDescriptor
{ {
public: public:
enum { L2Hys=0 }; enum { L2Hys=0 };
enum { DEFAULT_NLEVELS=64 };
CV_WRAP HOGDescriptor() : winSize(64,128), blockSize(16,16), blockStride(8,8), CV_WRAP HOGDescriptor() : winSize(64,128), blockSize(16,16), blockStride(8,8),
cellSize(8,8), nbins(9), derivAperture(1), winSigma(-1), cellSize(8,8), nbins(9), derivAperture(1), winSigma(-1),
histogramNormType(HOGDescriptor::L2Hys), L2HysThreshold(0.2), gammaCorrection(true) histogramNormType(HOGDescriptor::L2Hys), L2HysThreshold(0.2), gammaCorrection(true),
nlevels(DEFAULT_NLEVELS)
{} {}
CV_WRAP HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, CV_WRAP HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride,
Size _cellSize, int _nbins, int _derivAperture=1, double _winSigma=-1, Size _cellSize, int _nbins, int _derivAperture=1, double _winSigma=-1,
int _histogramNormType=HOGDescriptor::L2Hys, int _histogramNormType=HOGDescriptor::L2Hys,
double _L2HysThreshold=0.2, bool _gammaCorrection=false) double _L2HysThreshold=0.2, bool _gammaCorrection=false, int _nlevels=DEFAULT_NLEVELS)
: winSize(_winSize), blockSize(_blockSize), blockStride(_blockStride), cellSize(_cellSize), : winSize(_winSize), blockSize(_blockSize), blockStride(_blockStride), cellSize(_cellSize),
nbins(_nbins), derivAperture(_derivAperture), winSigma(_winSigma), nbins(_nbins), derivAperture(_derivAperture), winSigma(_winSigma),
histogramNormType(_histogramNormType), L2HysThreshold(_L2HysThreshold), histogramNormType(_histogramNormType), L2HysThreshold(_L2HysThreshold),
gammaCorrection(_gammaCorrection) gammaCorrection(_gammaCorrection), nlevels(_nlevels)
{} {}
CV_WRAP HOGDescriptor(const String& filename) CV_WRAP HOGDescriptor(const String& filename)
@ -429,6 +431,7 @@ public:
CV_PROP double L2HysThreshold; CV_PROP double L2HysThreshold;
CV_PROP bool gammaCorrection; CV_PROP bool gammaCorrection;
CV_PROP vector<float> svmDetector; CV_PROP vector<float> svmDetector;
CV_PROP int nlevels;
}; };

3
modules/objdetect/src/hog.cpp
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@ -872,11 +872,10 @@ void HOGDescriptor::detectMultiScale(
double scale0, int groupThreshold) const double scale0, int groupThreshold) const
{ {
double scale = 1.; double scale = 1.;
const int maxLevels = 64;
int levels = 0; int levels = 0;
vector<double> levelScale; vector<double> levelScale;
for( levels = 0; levels < maxLevels; levels++ ) for( levels = 0; levels < nlevels; levels++ )
{ {
levelScale.push_back(scale); levelScale.push_back(scale);
if( cvRound(img.cols/scale) < winSize.width || if( cvRound(img.cols/scale) < winSize.width ||