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preprocessing ~1.981 ms

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marina.kolpakova 2012-09-26 13:34:21 +04:00
parent 1917366528
commit 4d9c7c1012
2 changed files with 133 additions and 96 deletions
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54
modules/gpu/src/cuda/isf-sc.cu
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@ -40,6 +40,7 @@
// //
//M*/ //M*/
#include <opencv2/gpu/device/common.hpp>
// #include <icf.hpp> // #include <icf.hpp>
// #include <opencv2/gpu/device/saturate_cast.hpp> // #include <opencv2/gpu/device/saturate_cast.hpp>
// #include <stdio.h> // #include <stdio.h>
@ -54,9 +55,8 @@
// # define dprintf(format, ...) // # define dprintf(format, ...)
// #endif // #endif
// namespace cv { namespace gpu { namespace device { namespace cv { namespace gpu { namespace device {
namespace icf {
// namespace icf {
// enum { // enum {
// HOG_BINS = 6, // HOG_BINS = 6,
@ -66,33 +66,35 @@
// GREY_OFFSET = HEIGHT * HOG_LUV_BINS // GREY_OFFSET = HEIGHT * HOG_LUV_BINS
// }; // };
// __global__ void magToHist(const uchar* __restrict__ mag, // ToDo: use textures or ancached load instruction.
// const float* __restrict__ angle, const int angPitch, __global__ void magToHist(const uchar* __restrict__ mag,
// uchar* __restrict__ hog, const int hogPitch) const float* __restrict__ angle, const int angPitch,
// { uchar* __restrict__ hog, const int hogPitch, const int fh)
// const int y = blockIdx.y * blockDim.y + threadIdx.y; {
// const int x = blockIdx.x * blockDim.x + threadIdx.x; const int y = blockIdx.y * blockDim.y + threadIdx.y;
const int x = blockIdx.x * blockDim.x + threadIdx.x;
// const int bin = (int)(angle[y * angPitch + x]); const int bin = (int)(angle[y * angPitch + x]);
// const uchar val = mag[y * angPitch + x]; const uchar val = mag[y * hogPitch + x];
hog[((fh * bin) + y) * hogPitch + x] = val;
}
// hog[((HEIGHT * bin) + y) * hogPitch + x] = val; void fillBins(cv::gpu::PtrStepSzb hogluv, const cv::gpu::PtrStepSzf& nangle,
// } const int fw, const int fh, const int bins)
{
const uchar* mag = (const uchar*)hogluv.ptr(fh * bins);
uchar* hog = (uchar*)hogluv.ptr();
const float* angle = (const float*)nangle.ptr();
// void fillBins(cv::gpu::PtrStepSzb hogluv, const cv::gpu::PtrStepSzf& nangle) dim3 block(32, 8);
// { dim3 grid(fw / 32, fh / 8);
// const uchar* mag = (const uchar*)hogluv.ptr(HEIGHT * HOG_BINS);
// uchar* hog = (uchar*)hogluv.ptr();
// const float* angle = (const float*)nangle.ptr();
// dim3 block(32, 8); magToHist<<<grid, block>>>(mag, angle, nangle.step / sizeof(float), hog, hogluv.step, fh);
// dim3 grid(WIDTH / 32, HEIGHT / 8); cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
// magToHist<<<grid, block>>>(mag, angle, nangle.step / sizeof(float), hog, hogluv.step); }
// cudaSafeCall( cudaGetLastError() ); }
// cudaSafeCall( cudaDeviceSynchronize() ); }}}
// }
// }
// __global__ void detect(const cv::gpu::icf::Cascade cascade, const int* __restrict__ hogluv, const int pitch, // __global__ void detect(const cv::gpu::icf::Cascade cascade, const int* __restrict__ hogluv, const int pitch,
// PtrStepSz<uchar4> objects) // PtrStepSz<uchar4> objects)

175
modules/gpu/src/softcascade.cpp
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@ -49,17 +49,18 @@ cv::gpu::SoftCascade::SoftCascade() : filds(0) { throw_nogpu(); }
cv::gpu::SoftCascade::SoftCascade( const string&, const float, const float) : filds(0) { throw_nogpu(); } cv::gpu::SoftCascade::SoftCascade( const string&, const float, const float) : filds(0) { throw_nogpu(); }
cv::gpu::SoftCascade::~SoftCascade() { throw_nogpu(); } cv::gpu::SoftCascade::~SoftCascade() { throw_nogpu(); }
bool cv::gpu::SoftCascade::load( const string&, const float, const float) { throw_nogpu(); return false; } bool cv::gpu::SoftCascade::load( const string&, const float, const float) { throw_nogpu(); return false; }
void cv::gpu::SoftCascade::detectMultiScale(const GpuMat&, const GpuMat&, GpuMat&, const int, Stream) { throw_nogpu(); } void cv::gpu::SoftCascade::detectMultiScale(const GpuMat&, const GpuMat&, GpuMat&, const int, Stream) { throw_nogpu();}
#else #else
// #include <icf.hpp> // #include <icf.hpp>
// namespace cv { namespace gpu { namespace device { namespace cv { namespace gpu { namespace device {
// namespace icf { namespace icf {
// void fillBins(cv::gpu::PtrStepSzb hogluv,const cv::gpu::PtrStepSzf& nangle); void fillBins(cv::gpu::PtrStepSzb hogluv, const cv::gpu::PtrStepSzf& nangle,
// } const int fw, const int fh, const int bins);
// }}} }
}}}
// namespace { // namespace {
// char *itoa(long i, char* s, int /*dummy_radix*/) // char *itoa(long i, char* s, int /*dummy_radix*/)
@ -71,6 +72,16 @@ void cv::gpu::SoftCascade::detectMultiScale(const GpuMat&, const GpuMat&, GpuMat
struct cv::gpu::SoftCascade::Filds struct cv::gpu::SoftCascade::Filds
{ {
Filds()
{
plane.create(FRAME_HEIGHT * (HOG_LUV_BINS + 1), FRAME_WIDTH, CV_8UC1);
fplane.create(FRAME_HEIGHT * 6, FRAME_WIDTH, CV_32FC1);
luv.create(FRAME_HEIGHT, FRAME_WIDTH, CV_8UC3);
shrunk.create(FRAME_HEIGHT / 4 * HOG_LUV_BINS, FRAME_WIDTH / 4, CV_8UC1);
integralBuffer.create(shrunk.rows + 1 * HOG_LUV_BINS, shrunk.cols + 1, CV_32SC1);
hogluv.create((FRAME_HEIGHT / 4 + 1) * HOG_LUV_BINS, FRAME_WIDTH / 4 + 1, CV_32SC1);
}
// // scales range // // scales range
// float minScale; // float minScale;
// float maxScale; // float maxScale;
@ -85,19 +96,26 @@ struct cv::gpu::SoftCascade::Filds
// GpuMat features; // GpuMat features;
// GpuMat levels; // GpuMat levels;
// // preallocated buffer 640x480x10 + 640x480 // preallocated buffer 640x480x10 for hogluv + 640x480 got gray
// GpuMat dmem; GpuMat plane;
// // 160x120x10
// GpuMat shrunk; // preallocated buffer for floating point operations
// // 161x121x10 GpuMat fplane;
// GpuMat hogluv;
// temporial mat for cvtColor
GpuMat luv;
// 160x120x10
GpuMat shrunk;
// temporial mat for integrall
GpuMat integralBuffer;
// 161x121x10
GpuMat hogluv;
// // will be removed in final version // // will be removed in final version
// // temporial mat for cvtColor
// GpuMat luv;
// // temporial mat for integrall
// GpuMat integralBuffer;
// // temp matrix for sobel and cartToPolar // // temp matrix for sobel and cartToPolar
// GpuMat dfdx, dfdy, angle, mag, nmag, nangle; // GpuMat dfdx, dfdy, angle, mag, nmag, nangle;
@ -108,17 +126,18 @@ struct cv::gpu::SoftCascade::Filds
// icf::ChannelStorage storage; // icf::ChannelStorage storage;
// enum { BOOST = 0 }; // enum { BOOST = 0 };
// enum enum
// { {
// FRAME_WIDTH = 640, FRAME_WIDTH = 640,
// FRAME_HEIGHT = 480, FRAME_HEIGHT = 480,
// TOTAL_SCALES = 55, // TOTAL_SCALES = 55,
// CLASSIFIERS = 5, // CLASSIFIERS = 5,
// ORIG_OBJECT_WIDTH = 64, // ORIG_OBJECT_WIDTH = 64,
// ORIG_OBJECT_HEIGHT = 128, // ORIG_OBJECT_HEIGHT = 128,
// HOG_BINS = 6, HOG_BINS = 6,
// HOG_LUV_BINS = 10 LUV_BINS = 3,
// }; HOG_LUV_BINS = 10
};
// bool fill(const FileNode &root, const float mins, const float maxs); // bool fill(const FileNode &root, const float mins, const float maxs);
// void detect(cv::gpu::GpuMat objects, cudaStream_t stream) const // void detect(cv::gpu::GpuMat objects, cudaStream_t stream) const
@ -386,7 +405,8 @@ struct cv::gpu::SoftCascade::Filds
// scale = ::std::min(maxScale, ::expf(::log(scale) + logFactor)); // scale = ::std::min(maxScale, ::expf(::log(scale) + logFactor));
// // printf("level: %d (%f %f) [%f %f] (%d %d) (%d %d)\n", level.octave, level.relScale, level.shrScale, // // printf("level: %d (%f %f) [%f %f] (%d %d) (%d %d)\n", level.octave, level.relScale, level.shrScale,
// // level.scaling[0], level.scaling[1], level.workRect.x, level.workRect.y, level.objSize.x, level.objSize.y); // // level.scaling[0], level.scaling[1], level.workRect.x, level.workRect.y, level.objSize.x,
//level.objSize.y);
// // std::cout << "level " << sc // // std::cout << "level " << sc
// // << " octeve " // // << " octeve "
@ -423,8 +443,8 @@ bool cv::gpu::SoftCascade::load( const string& filename, const float minScale, c
if (!fs.isOpened()) return false; if (!fs.isOpened()) return false;
filds = new Filds; filds = new Filds;
// Filds& flds = *filds; Filds& flds = *filds;
// if (!flds.fill(fs.getFirstTopLevelNode(), minScale, maxScale)) return false; // if (!flds.fill(fs.getFirstTopLevelNode(), minScale, maxScale)) return false;
return true; return true;
} }
@ -432,15 +452,15 @@ bool cv::gpu::SoftCascade::load( const string& filename, const float minScale, c
void cv::gpu::SoftCascade::detectMultiScale(const GpuMat& colored, const GpuMat& /*rois*/, void cv::gpu::SoftCascade::detectMultiScale(const GpuMat& colored, const GpuMat& /*rois*/,
GpuMat& objects, const int /*rejectfactor*/, Stream s) GpuMat& objects, const int /*rejectfactor*/, Stream s)
{ {
// // only color images are supperted // only color images are supperted
// CV_Assert(colored.type() == CV_8UC3); CV_Assert(colored.type() == CV_8UC3);
// // // only this window size allowed // only this window size allowed
// CV_Assert(colored.cols == 640 && colored.rows == 480); CV_Assert(colored.cols == Filds::FRAME_WIDTH && colored.rows == Filds::FRAME_HEIGHT);
// Filds& flds = *filds; Filds& flds = *filds;
// #if defined USE_REFERENCE_VALUES #if defined USE_REFERENCE_VALUES
// cudaMemset(flds.hogluv.data, 0, flds.hogluv.step * flds.hogluv.rows); // cudaMemset(flds.hogluv.data, 0, flds.hogluv.step * flds.hogluv.rows);
// cv::FileStorage imgs("/home/kellan/testInts.xml", cv::FileStorage::READ); // cv::FileStorage imgs("/home/kellan/testInts.xml", cv::FileStorage::READ);
// char buff[33]; // char buff[33];
@ -452,57 +472,72 @@ void cv::gpu::SoftCascade::detectMultiScale(const GpuMat& colored, const GpuMat&
// GpuMat gchannel(flds.hogluv, cv::Rect(0, 121 * i, 161, 121)); // GpuMat gchannel(flds.hogluv, cv::Rect(0, 121 * i, 161, 121));
// gchannel.upload(channel); // gchannel.upload(channel);
// } // }
// #else #else
// GpuMat& dmem = flds.dmem; GpuMat& plane = flds.plane;
// cudaMemset(dmem.data, 0, dmem.step * dmem.rows); GpuMat& shrunk = flds.shrunk;
// GpuMat& shrunk = flds.shrunk; cudaMemset(plane.data, 0, plane.step * plane.rows);
// int w = shrunk.cols;
// int h = colored.rows / flds.storage.shrinkage;
// std::vector<GpuMat> splited; int fw = Filds::FRAME_WIDTH;
// for(int i = 0; i < 3; ++i) int fh = Filds::FRAME_HEIGHT;
// {
// splited.push_back(GpuMat(dmem, cv::Rect(0, colored.rows * (7 + i), colored.cols, colored.rows)));
// }
// GpuMat gray(dmem, cv::Rect(0, colored.rows * 10, colored.cols, colored.rows) ); GpuMat gray(plane, cv::Rect(0, fh * Filds::HOG_LUV_BINS, fw, fh));
// cv::gpu::cvtColor(colored, gray, CV_RGB2GRAY); //cv::gpu::cvtColor(colored, gray, CV_RGB2GRAY);
cv::gpu::cvtColor(colored, gray, CV_BGR2GRAY);
// //create hog //create hog
// cv::gpu::Sobel(gray, flds.dfdx, CV_32F, 1, 0, 3, 0.25); GpuMat dfdx(flds.fplane, cv::Rect(0, 0, fw, fh));
// cv::gpu::Sobel(gray, flds.dfdy, CV_32F, 0, 1, 3, 0.25); GpuMat dfdy(flds.fplane, cv::Rect(0, fh, fw, fh));
// cv::gpu::cartToPolar(flds.dfdx, flds.dfdy, flds.mag, flds.angle, true); cv::gpu::Sobel(gray, dfdx, CV_32F, 1, 0, 3, 0.125f);
cv::gpu::Sobel(gray, dfdy, CV_32F, 0, 1, 3, 0.125f);
// cv::gpu::multiply(flds.mag, cv::Scalar::all(1.0 / ::log(2)), flds.nmag); GpuMat mag(flds.fplane, cv::Rect(0, 2 * fh, fw, fh));
// cv::gpu::multiply(flds.angle, cv::Scalar::all(1.0 / 60.0), flds.nangle); GpuMat ang(flds.fplane, cv::Rect(0, 3 * fh, fw, fh));
// GpuMat magCannel(dmem, cv::Rect(0, colored.rows * 6, colored.cols, colored.rows)); cv::gpu::cartToPolar(dfdx, dfdy, mag, ang, true);
// flds.nmag.convertTo(magCannel, CV_8UC1);
// device::icf::fillBins(dmem, flds.nangle);
// // create luv // normolize magnitude to uchar interval and angles to 6 bins
// cv::gpu::cvtColor(colored, flds.luv, CV_BGR2Luv);
// cv::gpu::split(flds.luv, splited);
// GpuMat plane(dmem, cv::Rect(0, 0, colored.cols, colored.rows * Filds::HOG_LUV_BINS)); GpuMat nmag(flds.fplane, cv::Rect(0, 4 * fh, fw, fh));
// cv::gpu::resize(plane, flds.shrunk, cv::Size(), 0.25, 0.25, CV_INTER_AREA); GpuMat nang(flds.fplane, cv::Rect(0, 5 * fh, fw, fh));
// // fer debug purpose cv::gpu::multiply(mag, cv::Scalar::all(1.f / ::log(2)), nmag);
// // cudaMemset(flds.hogluv.data, 0, flds.hogluv.step * flds.hogluv.rows); cv::gpu::multiply(ang, cv::Scalar::all(1.f / 60.f), nang);
// for(int i = 0; i < Filds::HOG_LUV_BINS; ++i) //create uchar magnitude
// { GpuMat cmag(plane, cv::Rect(0, fh * Filds::HOG_BINS, fw, fh));
// GpuMat channel(shrunk, cv::Rect(0, h * i, w, h )); nmag.convertTo(cmag, CV_8UC1);
// GpuMat sum(flds.hogluv, cv::Rect(0, (h + 1) * i, w + 1, h + 1));
// cv::gpu::integralBuffered(channel, sum, flds.integralBuffer);
// }
// #endif // create luv
cv::gpu::cvtColor(colored, flds.luv, CV_BGR2Luv);
// cudaStream_t stream = StreamAccessor::getStream(s); std::vector<GpuMat> splited;
// // detection for(int i = 0; i < Filds::LUV_BINS; ++i)
{
splited.push_back(GpuMat(plane, cv::Rect(0, fh * (7 + i), fw, fh)));
}
cv::gpu::split(flds.luv, splited);
device::icf::fillBins(plane, nang, fw, fh, Filds::HOG_BINS);
GpuMat hogluv(plane, cv::Rect(0, 0, fw, fh * Filds::HOG_LUV_BINS));
cv::gpu::resize(hogluv, flds.shrunk, cv::Size(), 0.25, 0.25, CV_INTER_AREA);
fw /= 4;
fh /= 4;
for(int i = 0; i < Filds::HOG_LUV_BINS; ++i)
{
GpuMat channel(shrunk, cv::Rect(0, fh * i, fw, fh ));
GpuMat sum(flds.hogluv, cv::Rect(0, (fh + 1) * i, fw + 1, fh + 1));
cv::gpu::integralBuffered(channel, sum, flds.integralBuffer);
}
#endif
cudaStream_t stream = StreamAccessor::getStream(s);
// detection
// flds.detect(objects, stream); // flds.detect(objects, stream);
// // flds.storage.frame(colored, stream); // // flds.storage.frame(colored, stream);