Commit 83e7d3dd authored by marina.kolpakova's avatar marina.kolpakova

remove generic version of GPU channel computer.

parent 3c8e66d5
macro(ocv_glob_cuda_powered_module_sources)
file(GLOB_RECURSE lib_srcs "src/*.cpp")
file(GLOB_RECURSE lib_int_hdrs "src/*.hpp" "src/*.h")
file(GLOB lib_hdrs "include/opencv2/${name}/*.hpp" "include/opencv2/${name}/*.h")
file(GLOB lib_hdrs_detail "include/opencv2/${name}/detail/*.hpp" "include/opencv2/${name}/detail/*.h")
file(GLOB_RECURSE lib_device_srcs "src/*.cu")
set(device_objs "")
set(lib_device_hdrs "")
if (HAVE_CUDA AND lib_device_srcs)
ocv_include_directories(${CUDA_INCLUDE_DIRS})
file(GLOB_RECURSE lib_device_hdrs "src/cuda/*.hpp")
ocv_cuda_compile(device_objs ${lib_device_srcs})
source_group("Src\\Cuda" FILES ${lib_device_srcs} ${lib_device_hdrs})
if (lib_device_hdrs)
list(REMOVE_ITEM lib_int_hdrs ${lib_device_hdrs})
endif()
endif()
ocv_set_module_sources(${ARGN} HEADERS ${lib_hdrs} ${lib_hdrs_detail}
SOURCES ${lib_srcs} ${lib_int_hdrs} ${device_objs} ${lib_device_srcs} ${lib_device_hdrs})
source_group("Src" FILES ${lib_srcs} ${lib_int_hdrs})
source_group("Include" FILES ${lib_hdrs})
source_group("Include\\detail" FILES ${lib_hdrs_detail})
endmacro()
set(the_description "Soft Cascade detection and training")
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4310 -Wundef -Wmissing-declarations)
set(cuda_deps "")
set(cuda_include "")
if (NAVE_CUDA)
set(cuda_deps ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
endif()
ocv_add_module(softcascade opencv_core opencv_imgproc opencv_ml OPTIONAL ${cuda_deps})
if(HAVE_CUDA)
ocv_module_include_directories(${CUDA_INCLUDE_DIRS})
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef)
else()
ocv_module_include_directories()
endif()
ocv_glob_cuda_powered_module_sources()
ocv_create_module()
ocv_add_precompiled_headers(${the_module})
ocv_add_accuracy_tests()
ocv_add_perf_tests()
ocv_define_module(softcascade opencv_core opencv_imgproc opencv_ml)
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4310 -Wundef)
......@@ -219,7 +219,7 @@ class CV_EXPORTS ChannelsProcessor
public:
enum
{
GENERIC = 1 << 4,
// GENERIC = 1 << 4, does not supported
SEPARABLE = 2 << 4
};
......@@ -233,7 +233,7 @@ public:
// Param shrinkage is a resizing factor. Resize is applied before the computing integral sum
// Param bins is a number of HOG-like channels.
// Param flags is a channel computing extra flags.
static cv::Ptr<ChannelsProcessor> create(const int shrinkage, const int bins, const int flags = GENERIC);
static cv::Ptr<ChannelsProcessor> create(const int shrinkage, const int bins, const int flags = SEPARABLE);
virtual ~ChannelsProcessor();
......@@ -267,7 +267,7 @@ public:
// Param scales is a number of scales from minScale to maxScale.
// Param flags is an extra tuning flags.
SCascade(const double minScale = 0.4, const double maxScale = 5., const int scales = 55,
const int flags = NO_REJECT || ChannelsProcessor::GENERIC);
const int flags = NO_REJECT | ChannelsProcessor::SEPARABLE);
virtual ~SCascade();
......
......@@ -73,7 +73,7 @@ namespace
inline void ___cudaSafeCall(cudaError_t err, const char *file, const int line, const char *func = "")
{
//if (cudaSuccess != err) cv::gpu::error(cudaGetErrorString(err), file, line, func);
if (cudaSuccess != err) cv::gpu::error(cudaGetErrorString(err), file, line, func);
}
}
......@@ -545,98 +545,6 @@ inline void setZero(cv::gpu::GpuMat& m, cv::gpu::Stream& s)
m.setTo(0);
}
struct GenricPreprocessor : public cv::softcascade::ChannelsProcessor
{
GenricPreprocessor(const int s, const int b) : cv::softcascade::ChannelsProcessor(), shrinkage(s), bins(b) {}
virtual ~GenricPreprocessor() {}
virtual void apply(InputArray _frame, OutputArray _shrunk, cv::gpu::Stream& s = cv::gpu::Stream::Null())
{
const cv::gpu::GpuMat frame = _frame.getGpuMat();
_shrunk.create(frame.rows * (4 + bins) / shrinkage, frame.cols / shrinkage, CV_8UC1);
cv::gpu::GpuMat shrunk = _shrunk.getGpuMat();
channels.create(frame.rows * (4 + bins), frame.cols, CV_8UC1);
setZero(channels, s);
//cv::gpu::cvtColor(frame, gray, CV_BGR2GRAY, s);
createHogBins(s);
createLuvBins(frame, s);
//cv::gpu::resize(channels, shrunk, cv::Size(), 1.f / shrinkage, 1.f / shrinkage, CV_INTER_AREA, s);
}
private:
void createHogBins(cv::gpu::Stream& s)
{
static const int fw = gray.cols;
static const int fh = gray.rows;
fplane.create(fh * HOG_BINS, fw, CV_32FC1);
cv::gpu::GpuMat dfdx(fplane, cv::Rect(0, 0, fw, fh));
cv::gpu::GpuMat dfdy(fplane, cv::Rect(0, fh, fw, fh));
//cv::gpu::Sobel(gray, dfdx, CV_32F, 1, 0, sobelBuf, 3, 1, cv::BORDER_DEFAULT, -1, s);
//cv::gpu::Sobel(gray, dfdy, CV_32F, 0, 1, sobelBuf, 3, 1, cv::BORDER_DEFAULT, -1, s);
cv::gpu::GpuMat mag(fplane, cv::Rect(0, 2 * fh, fw, fh));
cv::gpu::GpuMat ang(fplane, cv::Rect(0, 3 * fh, fw, fh));
//cv::gpu::cartToPolar(dfdx, dfdy, mag, ang, true, s);
// normalize magnitude to uchar interval and angles to 6 bins
cv::gpu::GpuMat nmag(fplane, cv::Rect(0, 4 * fh, fw, fh));
cv::gpu::GpuMat nang(fplane, cv::Rect(0, 5 * fh, fw, fh));
//cv::gpu::multiply(mag, cv::Scalar::all(1.f / (8 *::log(2.0f))), nmag, 1, -1, s);
//cv::gpu::multiply(ang, cv::Scalar::all(1.f / 60.f), nang, 1, -1, s);
//create uchar magnitude
cv::gpu::GpuMat cmag(channels, cv::Rect(0, fh * HOG_BINS, fw, fh));
if (s)
s.enqueueConvert(nmag, cmag, CV_8UC1);
else
nmag.convertTo(cmag, CV_8UC1);
cudaStream_t stream = cv::gpu::StreamAccessor::getStream(s);
cv::softcascade::device::fillBins(channels, nang, fw, fh, HOG_BINS, stream);
}
void createLuvBins(const cv::gpu::GpuMat& colored, cv::gpu::Stream& s)
{
static const int fw = colored.cols;
static const int fh = colored.rows;
//cv::gpu::cvtColor(colored, luv, CV_BGR2Luv, s);
std::vector<cv::gpu::GpuMat> splited;
for(int i = 0; i < LUV_BINS; ++i)
{
splited.push_back(cv::gpu::GpuMat(channels, cv::Rect(0, fh * (7 + i), fw, fh)));
}
//cv::gpu::split(luv, splited, s);
}
enum {HOG_BINS = 6, LUV_BINS = 3};
const int shrinkage;
const int bins;
cv::gpu::GpuMat gray;
cv::gpu::GpuMat luv;
cv::gpu::GpuMat channels;
// preallocated buffer for floating point operations
cv::gpu::GpuMat fplane;
cv::gpu::GpuMat sobelBuf;
};
struct SeparablePreprocessor : public cv::softcascade::ChannelsProcessor
{
SeparablePreprocessor(const int s, const int b) : cv::softcascade::ChannelsProcessor(), shrinkage(s), bins(b) {}
......@@ -674,11 +582,7 @@ private:
cv::Ptr<cv::softcascade::ChannelsProcessor> cv::softcascade::ChannelsProcessor::create(const int s, const int b, const int m)
{
CV_Assert((m && SEPARABLE) || (m && GENERIC));
if (m && GENERIC)
return cv::Ptr<cv::softcascade::ChannelsProcessor>(new GenricPreprocessor(s, b));
CV_Assert((m && SEPARABLE));
return cv::Ptr<cv::softcascade::ChannelsProcessor>(new SeparablePreprocessor(s, b));
}
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment